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Fallback File Ops

OrganizationPopular
HKUDS
fallback-file-ops

Use run_shell as fallback when execute_code_sandbox or shell_agent fail on filesystem operations

Overview

PublisherHKUDS
RepositoryOpenSpace
Skill namefallback-file-ops
Stars
7.7K
Forks
918
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by HKUDS on GitHub. Read the source before you install it.

Installation

Install the Fallback File Ops AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/HKUDS/OpenSpace.git /tmp/OpenSpace
mkdir -p .claude/skills
cp -r /tmp/OpenSpace/benchmarks/gdpval/skills/fallback-file-ops .claude/skills/fallback-file-ops
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fallback File Ops in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Fallback File Ops on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Fallback File Ops is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Fallback File Operations

Purpose

When execute_code_sandbox or shell_agent fail with 'unknown error' on filesystem operations, fall back to run_shell with explicit mkdir and file write commands. This hybrid approach is more reliable for creating complex project structures.

When to Apply

  • execute_code_sandbox returns 'unknown error' on file/directory creation
  • shell_agent fails to write files or create nested directories
  • You need to create complex project structures with multiple levels

Procedure

Step 1: Detect Tool Failure

Monitor for these failure patterns:

  • Error message contains "unknown error"
  • File operations silently fail (file not created)
  • Directory creation returns success but directory doesn't exist

Step 2: Switch to run_shell

When failures occur, immediately switch to run_shell for filesystem operations:

bash
# Create directory structure explicitly
run_shell: mkdir -p /path/to/nested/directory

# Write files using shell redirection or echo
run_shell: echo "content" > /path/to/file.txt

# Or use cat with heredoc for multi-line files
run_shell: cat > /path/to/file.txt << 'EOF'
line 1
line 2
EOF

Step 3: Verify Creation

After each operation, verify the file/directory was created:

bash
run_shell: ls -la /path/to/created/item
run_shell: test -f /path/to/file && echo "File exists"
run_shell: test -d /path/to/dir && echo "Directory exists"

Step 4: Continue with Hybrid Approach

  • Use run_shell for all filesystem operations (mkdir, write, copy, move)
  • Continue using execute_code_sandbox or shell_agent for code execution, compilation, or other non-filesystem tasks
  • Document which tool handles which operation for clarity

Example: Creating Project Structure

yaml
# Failed attempt with execute_code_sandbox
execute_code_sandbox: create directory src/components

# Fallback with run_shell
run_shell: mkdir -p src/components
run_shell: mkdir -p src/utils
run_shell: mkdir -p tests/unit
run_shell: echo "// Component file" > src/components/Button.tsx
run_shell: echo "// Utility file" > src/utils/helpers.ts

Best Practices

  1. Be explicit: Always use full paths or confirm working directory
  2. Create parent directories: Use mkdir -p for nested structures
  3. Verify before proceeding: Check files exist before dependent operations
  4. Log tool switches: Note when you fall back to run_shell for debugging
  5. Batch operations: Group related file operations in consecutive run_shell calls

Common Pitfalls

  • Don't assume filesystem state after tool failure
  • Don't mix tools for the same file operation (pick one and stick with it)
  • Don't skip verification steps when using fallback

Frequently asked questions

What does the Fallback File Ops AI skill do?

Use run_shell as fallback when execute_code_sandbox or shell_agent fail on filesystem operations

Why use Fallback File Ops on TypingMind?

Because you install it once and use it with any model. Fallback File Ops is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Fallback File Ops in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/fallback-file-ops. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Fallback File Ops?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Fallback File Ops?

As many as you like. As long as a model supports skills, you can use Fallback File Ops with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Fallback File Ops AI skill free?

Yes. It is published on GitHub by HKUDS under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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